Regional Water Quality Management Research Articles

Hydrochemical characterization and health risk assessment of shallow groundwater in a northern coalfield of Anhui Province, China

In a global context, the hydrochemical characteristics of shallow groundwater in coalfields exhibit high degrees of diversity and complexity that are rooted in the intricate interplay of geological variations, diverse climatic conditions, and extensive human activities. The specific types and concentrations of ions, such as Ca2+, Cl−, and NO3−, show stark differences across geographical regions. Given the crucial roles of coalfields as energy suppliers, the potential environmental contamination risks posed by mining activities to groundwater cannot be overlooked as such pollution directly impacts human health and ecological safety. This study focuses on the Huainan coal mining area in northern Anhui Province (China), where shallow groundwater samples were systematically collected and analyzed to determine the hydrochemical characteristics and ascertain the water quality status. By integrating hydrogeochemical analysis techniques with inverse modeling methods, it was revealed that the groundwater in this region is predominantly HCO3-Ca type, exhibiting weak alkaline characteristics. The formation mechanisms are primarily governed by silicate rock weathering and mineral dissolution–precipitation processes, albeit with discernible influences from human activities. PHREEQC simulations were used to further confirm the precipitation tendencies of minerals like calcite, dolomite, and fluorite as well as the significant dissolution characteristics of halite. The inverse modeling pathway analysis reveals specific hydrochemical processes along different paths: paths I and IV are notably dominated by Ca2+ dissolution–precipitation and cation exchange–adsorption processes, whereas paths II and III are closely associated with the precipitation of calcium montmorillonite as well as dissolution of kaolinite, calcite, quartz, and mineral incongruents. Moreover, evaluations based on the entropy-weighted water quality index (EWQI) indicated overall positive trends of the groundwater quality indicators within the Huainan mining area, reflecting the effectiveness of regional water quality management efforts and providing a scientific basis for future water quality protection and improvement strategies. In summary, this study not only deepens our understanding of the groundwater chemistry in the Huainan coal mining area but also underscores the importance of scientifically assessing and managing groundwater resources to address the environmental challenges potentially arising from coal mining activities.

Environmental Risk Assessment of the Harbin Section of the Songhua River Basin Based on Multi-Source Data Fusion

Surface water is a vital resource for human survival. However, economic and social development has resulted in significant pollutants from human activities, causing environmental pollution in watersheds. This pollution has had a profound impact on the surface water environment. However, limited studies have been conducted on the environmental risk evaluation of the watershed. In this study, we accounted for agricultural, industrial, and domestic source discharges in the districts and counties of the Harbin section of the Songhua River Basin for 2021. Data were collected from Statistical Yearbooks and governmental departments, and the characteristics of pollutant discharges in Harbin’s districts and counties were analyzed. Subsequently, we employed the Back Propagation neural network optimization method, combining remote sensing data, accounting data, pollution discharge data from each district and county, and economic and social data from the Statistical Yearbook and literature. This fusion of multiple data sources facilitated the construction of a watershed environmental risk evaluation system. The analysis considered four levels: economic and social, resource load, environmental infrastructure, and pollution discharge. Via this comprehensive evaluation, we identified the reasons for environmental risks in the water environment of the Harbin section of the Songhua River Basin. The evaluation results indicate that Nangang District, Xiangfang District, and Pingfang District face a higher risk to the water environment. Consequently, recommendations for mitigating water environment risks in these areas and across Harbin City are presented. The research methods and findings in this paper contribute valuable insights for developing control strategies to manage water quality in critically polluted areas of the Harbin section of the Songhua River Basin, providing a scientific foundation for regional river water quality management studies.

Evaluation of surface water quality in Heilongjiang Province, China: Based on different quantities of water quality indicators

Accurately evaluating surface water quality grade (WQG) is of great significance in improving the efficiency of regional water quality management. Based on seven main surface water quality indicators (including dissolved oxygen (DO), chemical oxygen demand (COD), permanganate index (CODMn), ammonia nitrogen (NH4+-N), fluoride (FL), total phosphorus (TP) and total nitrogen (TN)) data from 910 measuring points in Heilongjiang Province from May to August 2017, an improved Nemerow index method (IN method) based on combined weighting was constructed, and the WQG was evaluated. On this basis, the multiple linear or non-linear regression models (MLR or MNR) under different quantities of water quality indicators were established, and the prediction results were evaluated. Results show that: 1) WQG in Heilongjiang Province above grade III accounts for more than 92.6%, evaluated by the IN method; 2) The accuracy of WQG evaluated by MLR based on different quantities of water quality indicators are maintained at 77%-90% and decreases with the increase of the number of water quality indicators (N), which may be related to the selected combination of water quality indicators and key water pollutants. The accuracy is improved by 3.9%-17.4% for MNR as compared to MLR, and especially the accuracy can reach as high as 95.6% when N is 5; 3) Compare to the MLR, the MNR is less affected by the data fluctuation characteristics, and performs best when N is 5 under both the great and small data fluctuations, with an accuracy of 85% and 90%, respectively. 4) TN (0.72), NH4+-N (0.41), and CODMn (0.33) are significantly related to the WQG. COD is a key parameter affecting the stability and uncertainty of MLR and MNR. These results provide a simple and reliable method for accurately evaluating the surface WQG, which have important guiding significance for decision-makers and researchers in water environment protection and agricultural water fertilizer management in Heilongjiang Province.

Characterizing spatial dependence of boron, arsenic, and other trace elements for Permian groundwater in Northern Anhui plain coal mining area, China, using spatial autocorrelation index and geostatistics.

Anthropogenic and geological factors play an essential role in the variability of groundwater quality, resulting in a weak spatial dependence of groundwater trace elements. Thus, it is an essential study to investigate the factors affecting groundwater quality and its spatial abundance of trace elements (including As, B, and other metalloids). In this study, samples are obtained from a Permian sandstone fracture aquifer in a coal mining area. A multivariate statistical analysis, hydrogeochemistry modeling, and spatial autocorrelation analysis were used to analyze the data. The results showed that Moran index was positive for all trace elements, which had good spatial autocorrelation. The Local indicators of spatial association (LISA) indicated that trace elements were clustered. The hydrogeochemical modeling results indicated that the precipitation and stability of iron-phase minerals, such as rhodochrosite and arsenic (As) absorption on the surface of iron-phase minerals in the aquifer, may limit concentrations in the southern region. The spatial autocorrelations of both As and Boron (B) were positive (high-high) in the western areas, indicating that As contamination occurred from both natural geological causes and human coal mining activities. In contrast, B contamination was mainly linked to the influence of human agricultural or industrial activities. Over 96% of the groundwater concentrations of As (10μg/L) and B (300μg/L) in the study area exceeded World Health Organization (WHO) limits. Overall, the results of this work could help decision-makers involved in regional water quality management visualize disperse zones where specific anthropogenic and geological processes may threaten groundwater quality.

A Revised Method of Surface Water Quality Evaluation Based on Background Values and Its Application to Samples Collected in Heilongjiang Province, China

In China, the use of certain standards to evaluate surface water quality in areas with high background values due to natural factors rather than to human activities results in water quality underestimation and thus affects regional water quality management and decision-making. Herein, we examined river source water function zones of the Heilongjang province characterised by high background values and analysed the corresponding water quality data acquired in 2011–2016. The examined samples featured elevated chemical oxygen demand (COD), permanganate index (CODMn), and ammonia nitrogen (NH3-N) levels, which indicated that water quality was affected by the natural environment. The concentrations of background pollutants almost exceeded the limits stipulated by regional surface water quality standards and exhibited strong spatiotemporal variability. A three-step discrimination method including single index recognition, limiting factors, and a synthetic index was proposed to distinguish the background area among these zones for determining background values, and 10 complete background areas were identified. The background values of COD, CODMn, and NH3-N for the entire area were determined based on the data acquired during background area monitoring. Finally, considering the present procedure of water quality evaluation in China (single factor exponential method), a revised method based on background values was suggested. Thus, the evaluation results objectively and accurately reflect the regional water quality situation and therefore provide a scientific basis for the development of a better water quality assessment and management system in China.

Redox hydrogeochemistry of organic rich floodplain exemplified by Ammer river

Diffusive groundwater pollution caused by agricultural and atmospheric inputs is a pressing issue in environmental management worldwide. Various researchers have studied nitrate contamination since the substantial increase of nitrogen fertilization in agriculture starting in the second half of the 20th century. This study addresses large scale reactive solute transport in typical landscapes and aquifers exemplified by geological analogues of southwestern Germany.. Fate of nitrate and other solutes (e.g. agricultural nitrate, ammonium, natural sulfate and dissolved organic carbon) was studied in a typical small river floodplain. Reactive transport model of Ammer river floodplain shows that agriculture nitrate is reduced rapidly in the Ammer floodplain sediments. However, there is a potential for geogenic production of ammonium in sediment layers high in organic carbon and peat, which might be a major source of nitrate in the drains. Part of the nitrate in drains and creeks in the Ammer valley thus could be of geogenic origin. Such findings are relevant for regional land and water quality management.

Robust Linear Programming and Its Application to Water and Environmental Decision-Making under Uncertainty

In this study, we introduce a robust linear programming approach for water and environmental decision-making under uncertainty. This approach is of significant practical utility to decision makers for obtaining reliable and robust management decisions that are “immune” to the uncertainty attributable to data perturbations. The immunization guarantees that the chosen robust management plan will be implementable with no violation of the mandatory constraints of the problem being studied—i.e., natural resource supply constraint, environmental carrying capacity constraint, environmental pollution control constraint, etc.—and that the actual value of the objective will be no worse than the given estimation if the perturbations of data fall within the specified uncertainty set. A simplified example in regional water quality management is provided to help water and environmental practitioners to better understand how to implement robust linear programming from the perspective of application, as well as to illustrate the significance and necessity of implementing robust optimization techniques in real-world practices. Robust optimization is a growing research field that requires more interdisciplinary research efforts and engagements from water and environmental practitioners. Both may benefit from the advances of management science.

Effective Cross-Border Monitoring Systems for Waterborne Microbial Pathogens

This book provides a real-world analysis of how to quantify and prioritize water-based microbial threats to human health, how to design data collection systems that truly support management decisions, and how to build a comprehensive monitoring program when dealing with cross-boundary issues.International borders and cross-boundary issues complicate water resource management. Even if nations or jurisdictions agree on the nature and source of the problem, differing legal frameworks complicate cross-border management, as the procedural steps and time necessary to implement a solution vary among entities. Waterborne pathogens transcend political boundaries and challenge the use of traditional political jurisdictions in meeting public policy objectives to protect human health. Disease outbreaks caused by waterborne pathogens continue to occur, even in the developed world.There has been a pronounced trend toward new and increasingly complex institutions and policies to address regional water quality management issues. However, many questions continue to arise regarding the effective management of regional resources. These questions include how to design effective monitoring strategies and what can be learned from previous successes and failures. The Laurentian Great Lakes offers a model system for exploring these questions.This book will be a valuable reference source for researchers and graduate students working in environmental science, microbiology, engineering, and biological sciences, as well as all those concerned with water quality monitoring programs.ISBN: 9781780401898 (eBook)ISBN: 9781843391692 (Print)

Development of an inexact two-stage stochastic model with downside risk control for water quality management and decision analysis under uncertainty

Water quality management along rivers involves making water-allocation plans, establishing water quality goals, and controlling pollutant discharges, which is complicated itself but further challenged by existence of uncertainties. In this study, an inexact two-stage stochastic downside risk-aversion programming (ITSDP) model is developed for supporting regional water resources allocation and water quality management problems under uncertainties. The ITSDP method is a hybrid of interval-parameter programming, two-stage stochastic programming, and downside risk measure to tackle uncertainties described in terms of interval values and probability distributions. A water quality simulation model was provided for reflecting the relationship between the water resources allocation, wastewater discharge, and environmental responses. The proposed approach was applied to a hypothetical case for a shared stream water quality management with one municipal, three industrial and two agricultural sectors. A number of scenarios corresponding to different river inflows and risk levels were examined. The results demonstrated that the model could effectively communicate the interval-format and random uncertainties, and risk-aversion into optimization process, and generate a trade-off between the system economy and stability. They could be helpful for seeking cost-effective management strategies under uncertainties, and gaining an in-depth insight into the water quality management system characteristics, and make cost-effective decisions.

Regional Water Quality Management in an Urban and Petrochemical Intensive Area of Canada

Regional Water Quality Management in an Urban and Petrochemical Intensive Area of Canada

Lessons Learned in Developing Social Indicators for Regional Water Quality Management

This article outlines a process for developing social indicators for regional resource management programs. Insights and lessons are drawn from experience developing indicators for the social dimensions of water quality programs addressing non-point-source pollution. The project driving these insights originated with a charge from regional leaders of a U.S. Environmental Protection Agency (EPA) water quality program to a project team comprised of participants from land grant universities within the region. We believe the indicator development process from that experience could be applied in other regions to address a variety of resource management issues. Key lessons learned through this process include the value of building stakeholder capacity for using social data, the importance of developing a conceptual framework to guide indicator selection, and the importance of selecting a small set of core indicators.

An environmental sustainability based budget allocation system for regional water quality management

A budget allocation system for regional water quality management to achieve environmental sustainability was developed in this study to assist a local authority with making appropriate budget allocations for improving Regional Water Environmental Sustainability (RWES) in an efficient manner. The system consists of visions and goals, RWES indicators, and an analysis of budget allocation versus RWES. Visions and goals define task priorities for improving water environmental sustainability. Indicators are used to measure the progress of related tasks toward RWES goals. These indicators are classified by the Driving Force-State-Response (DSR) framework to facilitate the analysis of relationships among indicators. Linkages between budget allocation and indicators are also analyzed, and the result is used to assess whether the available budget is allocated properly to raise the RWES. The applicability of the system is demonstrated by a case study involving a local environmental protection authority.

Regional water quality management for the Karun–Dez River basin, Iran

AbstractTo achieve water quality goals in a river basin, a water quality management model (WQMM) has been developed through the geographic information system (GIS) approach and a mathematical water quality model. The developed model has been applied to the Karun and Dez Rivers, where water quality has decreased due to heavy pollutant loads from Khuzestan province cities and surrounding areas. Pollution sources, land use, geographic features and measured water quality data of the river basin were incorporated into the Arc‐View GIS database. With the database, the management model calculated management type and management cost for each management project in the river basin. Until now, river management policy for polluted rivers in Iran first penalizes pollution sources and then constructs treatment plants for the pollution sources whose wastewater is released untreated and for which the wastewater quality goal of the Iranian Department of Environment is not met. Different management projects with a time programme were proposed and they were compared with the results of the river quality without any management approach. It became clear that the results based on the management approach were much better than those for the unmanaged condition from the viewpoint of the achievement of water quality goals and cost optimization.

Regional water quality management for the Dong Nai River Basin, Vietnam

A three-year study that started solely as an industrial pollution reduction effort in Dong Nai Province of Vietnam expanded into an ongoing regional river basin water quality management effort. The project was a cooperative effort between the United Nations (UNDP and UNIDO) and the Federal and Provincial governments in Vietnam. A comprehensive approach was used to assess the impacts and strategies for reducing industrial, municipal and agricultural pollution to the water, air and land. The strategy was based upon use of knowledge in four subject areas, economics, ecology, technology and institutions, integrated within a framework for regional environmental quality management, sometimes called Areawide Environmental Quality Management (AEQM). Dong Nal Province encompasses a major developing area immediately north of Ho Chi Minh City. The land area chosen for the AEQM study is the 1,400 square kilometre region in and around Bien Hoa that drains into the Dong Nai River. The Dong Nai River serves many purposes including navigation, fisheries and a water supply for both the Province and Ho Chi Minh City. Extensive industrial and residential development was underway and was projected to increase in the coming decade. A strategy for the control of pollution from liquid, gaseous and solid wastes for the period 1998 to 2010 in Dong Nai Province was developed.

MULTIPLE CRITERIA ANALYSIS FOR WATER QUALITY MANAGEMENT IN THE NITRA BASIN1

ABSTRACT: This paper presents the implementation of one element of a decision support system (DSS) for regional water quality management, applied to the Nitra River Basin in Slovakia. A model‐based, aspiration‐led methodology for multicriteria decision support has been used for the study. Several reusable, modular software tools have been developed and implemented: a problem‐specific generator to produce the core part of the mathematical programming model, tools for the generation and interactive modification of multicriteria problems, and a solver for the resulting mixed‐integer optimization problem. Provided in the paper are the following: a complete formulation of the mathematical model (including the imbedded water quality model), a summary of the aspiration‐reservation‐led multiple criteria optimization approach applied to decision support, and an overview of results that illustrate the applied approach and provide some interesting insights to the case study.

Oregon, USA, ecological regions and subregions for water quality management

To aid in producing a protection and management strategy for the freshwater resources of Oregon, USA, we have defined an initial set of ecological regions and subregions of the state that organize the spatial similarities and differences in water quality. We have delineated and mapped these subregions using existing maps of ecological regions, maps of selected environmental characteristics, remote sensing imagery, and descriptive literature. To help in interpreting the resulting map, a unique approach to mapping regions is used. We have described the relative widths of regional boundaries, and we ranked the characteristics used in determining them. Water quality managers in Oregon intend to apply these subregions as an organizational framework for data display and reporting, prioritizing monitoring and pollution control strategies, developing biological criteria for water quality standards, and developing other regional water quality management approaches.

Development and application of a model for regional water quality management

A mathematical model has been developed for determining the optimal extent of regional water and wastewater treatment and wastewater diversion schemes in a river basin. Systems optimization was applied to minimize the overall cost of those schemes, taking into consideration the stream assimilative capacity and the prescribed levels of the surface water quality parameters. The model was tested in a real situation, determining the minimum cost, size and optimal location of the treatment scheme to be built in the River Ave basin in Portugal.

Application of an efficient search technique for solving optimal regional water quality management problems

Abstract This article presents a simple yet effective search algorithmic method for solving regional water quality management problems. Essentially, the algorithm assigns the amount of wastewater flow to be treated at each treatment plant together with the associated level of treatment. When necessary this set of assigned values is adjusted appropriately (by raising the treatment efficiency of. and/or reduction of wastewater quantity to be treated by the treatment plant concerned), so that all the physical and water quality constraints are satisfied. Optimization is achieved by the use of a Random Polyhedron Search (RPS) algorithm which identifies progressively superior solutions. The paper comprises two parts: the first, in which feasibility is confined to treatment plant/transfer capacities, and the second, in which constraints relating to the in-stream quality of the receiving water are incorporated.

Regional Investment Functions of Material Infrastructure: Theoretical Issues and Selected Empirical Case Studies

In this paper a survey is given of the theoretical contributions essential for the derivation of regional investment functions of material infrastructure. A basic distinction is made between models of investment volume (level models) and investment-programming models (structure models). Investment functions may also be obtained from structure models by parametric programming that may be subsumed under those types of functions stemming from level models. In addition, empirical research on investment functions in selected fields of regional water-quality management, electricity supply, and provision of telephone services is summarized with respect to the main theoretical approaches—the accelerator models and the neoclassical cost model. To a substantial extent this research uses unpublished data for regression analysis.

Coupled optimization-simulation water quality model for regional water quality management

The objective pursued in water quality management is to secure water qualities such that marginal cost of the cleaning water equals the accuring marginal benefits. It is the purpose of this paper to show how the methods of system analysis may be used to plan more economical new pollution control facilities or how to upgrade existing systems. The particular problem investigated is the following: Given a region with a number of industries and/or municipalities, where should one build treatment plants and will be necessary levels that total regional cost of waste water treatment is minimum. To approach these problems, a stream water quality simulation is linked with a treatment cost minimization model in order to capitalize on the unique adventage of each in managing river basin water quality.